Frontiers in Population Biology using Ancient DNA
Uma Ramakrishnan, National Centre for Biological Sciences, Bangalore
Genetic variation is the currency for future evolution or change. Genetic variation also holds the key to understanding a populations’ evolutionary history. For example, such approaches have helped us understand that modern humans probably evolved in Africa and migrated to the rest of the world subsequently. Unfortunately, we often reconstruct recent processes that upset the genetic equilibrium of a population (like population growth or gene flow) and miss the more ancient processes, since their genetic signature is lost. The only way to investigate evolutionary history through time is to incorporate temporal genetic data into our analyses. Ancient DNA extracted from paleontological remains allows us to investigate population processes through time. Since most analysis methods do not incorporate data from multiple points in time, temporal data is a challenge to interpret. In my talk, I start by review existing analysis methods and their weaknesses. Further, I present a novel, simulation-based approach for the analysis of temporal genetic data. I then illustrate application of this approach using real ancient DNA data, and compare it to results obtained from other approaches. The novel approach allows more model flexibility, and I conclude by discussing potential problems with such flexibility and possible solutions.
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